Classification of Blood Cell Types Using CNN - Navya, D; Krishna, E; Rajaram, Dr. J; Raju, S (The journal of contemporary issues in business and government, 2020)
White blood cells, commonly referred to as leukocytes, play a critical part in human immunity development and maintenance. Classifying White Blood Cells plays a critical function in diagnosing sickness in a person. Using the classification, disorders including infections, allergies, anaemia, leukaemia, cancer, and the Acquired Immune Deficiency Syndrome (AIDS), which are caused by aberrations in the immune system, may be more accurately identified and treated as a result. To help haematologists identify the kind of White Blood Cells present in the human body and uncover the root cause of disorders, this categorization is necessary. There is now a lot of study being done in this area. A deep learning technology called Convolution Neural Networks (CNN) will be used to classify WBC pictures into four subtypes, namely neutrophil, eosinophil, lymphocyte, and monocyte, since classifying WBCs has enormous potential. In this work, we’ll present the results of a number of experiments on the Blood Cell Classification and Detection (BCCD) dataset, which we used to train CNNs.